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A Time Attention based Fraud Transaction Detection Framework [article]

Longfei Li, Ziqi Liu, Chaochao Chen, Ya-Lin Zhang, Jun Zhou, Xiaolong Li
2020 arXiv   pre-print
In this work, we present a novel method for detecting fraud transactions by leveraging patterns from both users' static profiles and users' dynamic behaviors in a unified framework.  ...  To address and explore the information of users' behaviors in continuous time spaces, we propose to use time attention based recurrent layers to embed the detailed information of the time interval, such  ...  the final training of the fraud transactions detection model.  ... 
arXiv:1912.11760v2 fatcat:6ksgrgsh2bafxk62jzyjash3g4

Spatio-Temporal Attention-Based Neural Network for Credit Card Fraud Detection

Dawei Cheng, Sheng Xiang, Chencheng Shang, Yiyi Zhang, Fangzhou Yang, Liqing Zhang
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Therefore, in this work, we propose a spatial-temporal attention-based neural network (STAN) for fraud detection.  ...  Contemporary methods apply machine learning-based approaches to detect fraudulent behavior from transaction records.  ...  The Proposed Approaches In this section, we first introduce the framework of a spatio-temporal attention-based neural model.  ... 
doi:10.1609/aaai.v34i01.5371 fatcat:qp5glvkjzvf3njbexspewwi65q

TeGraF

Shivshankar Reddy, Pranav Poduval, Anand Vir Singh Chauhan, Maneet Singh, Sangam Verma, Karamjit Singh, Tanmoy Bhowmik
2021 Proceedings of the Second ACM International Conference on AI in Finance  
To this effect, this research proposes a novel framework TeGraF for detecting fraudulent transactions by modeling temporal and structural features from a given input.  ...  An accurate fraud detection algorithm will help in identifying fraudulent transactions, thus facilitating immediate response and dispute resolution.  ...  [26] surveyed and formulated a graph based anomaly detection framework to capture a variety of frauds.  ... 
doi:10.1145/3490354.3494383 fatcat:shlh7hmbnbc7fgk4yehmxfuuqy

Transaction Fraud Detection Using GRU-centered Sandwich-structured Model [article]

Xurui Li, Wei Yu, Tianyu Luwang, Jianbin Zheng, Xuetao Qiu, Jintao Zhao, Lei Xia, Yujiao Li
2018 arXiv   pre-print
Meanwhile, fraudsters are continually refining their tricks, making rule-based fraud detection systems difficult to handle the ever-changing fraud patterns.  ...  Nevertheless, there is always a contradiction that most methods are irrelevant to transaction sequence, yet sequence-related methods usually cannot learn information at single-transaction level well.  ...  Entire Fraud Detection Model Based on "WBW" Sequence Learning Architecture Final fraud detection model can then be trained using a top-layer classifier based on the optimized eigenvectors V op .  ... 
arXiv:1711.01434v3 fatcat:r3hd4z3a6ngtzc6wupwowpcdsm

Improved Deep Forest Mode for Detection of Fraudulent Online Transaction

Mian Huang, Lizhi Wang, Zhaohui Zhang
2020 Computing and informatics  
In this paper, aiming at sample imbalance and strong concealment of online transactions, we enhance the original deep forest framework to propose a deep forest-based online transaction fraud detection  ...  As the rapid development of online transactions, transaction frauds have also emerged seriously. The fraud strategies are characterized by specialization, industrialization, concealment and scenes.  ...  [20] present CLUE framework, a novel DL-based transaction fraud detection system.  ... 
doi:10.31577/cai_2020_5_1082 fatcat:4udkvbwobvc75mrnxioi3ztaku

Location based FDS Framework

Jong Bae Kim, Myung Jin Bae
2018 International Journal of Engineering & Technology  
The FDS (Fraud Detection System) is a technological approach to prevent financial accidents by detecting abnormal behavior in financial transactions.  ...  In addition, we propose a model that can improve the accuracy of abnormal transaction detection by using GPS information of user.  ...  Fraud detection systems are based on misuse detection and anomaly detection. It is based on the concept of (Intrusion Detection System) misuse detection system and anomaly detection system.  ... 
doi:10.14419/ijet.v7i3.33.18527 fatcat:uzwbd7g37vbornhdoo7oqu2lve

A Scalable Approach for Fraud Detection in Online E-Commerce Transactions with Big Data Analytics

Hangjun Zhou, Guang Sun, Sha Fu, Wangdong Jiang, Juan Xue
2019 Computers Materials & Continua  
.; Xu, W. (2017): Session-based fraud detection in online e-commerce transactions using recurrent neural networks.  ...  Zheng, L.; Liu, G.; Yan, C.; Jiang, C. (2018): Transaction fraud detection based on total order relation and behavior diversity.  ...  A web service framework for credit card fraud detection in nearly real-time is described in Tselykh et al. [Tselykh and Petukhov (2015) ]. Paper Phulari et al.  ... 
doi:10.32604/cmc.2019.05214 fatcat:h6zxqlzuijfcdmdvvwp2mbsjwe

A Framework for Occupational Fraud Detection by Social Network Analysis

Sanni Lookman, Selmin Nurcan
2015 International Conference on Advanced Information Systems Engineering  
This paper introduces the OFD -Occupational Fraud Detection framework, based on formal social network analysis and semantic reasoning principles by taking a design science research perspective.  ...  This paper explores issues related to occupational fraud detection.  ...  Secondly, the dynamic nature of fraud makes detection challenging for the traditional rule based algorithms.  ... 
dblp:conf/caise/LookmanN15 fatcat:gxpzrc7clvfgpj2glizonz6kbq

Intelligent Financial Fraud Detection Practices: An Investigation [article]

J. West, Maumita Bhattacharya, R. Islam
2015 arXiv   pre-print
This paper presents a comprehensive investigation on financial fraud detection practices using such data mining methods, with a particular focus on computational intelligence-based techniques.  ...  Classification of the practices based on key aspects such as detection algorithm used, fraud type investigated, and success rate have been covered.  ...  Finally, further research into the differences between each type of financial fraud could lead to a generic framework which would greatly enhance the scope of intelligent detection methods for this problem  ... 
arXiv:1510.07165v1 fatcat:jgvqfrowwnf27adzulock66sve

Credit Card Fraud Detection using Machine Learning

2019 International Journal of Engineering and Advanced Technology  
When credit card transactions become a common mode of payment, machine learning has been based on handling the credit card fraud problem.  ...  This paper investigates naïve bayesian, k-nearest neighbor's performance on highly skewed credit card fraud based on genetic and optimization algorithm to determine the fraudulent transaction using credit  ...  In such a case a future enhancement may be based on new multiple models with varying access pattern needs attention to improve the effectiveness.  ... 
doi:10.35940/ijeat.b4957.129219 fatcat:4khkmer67bczfcir2tnhg2qihe

Intelligent Financial Fraud Detection Practices: An Investigation [chapter]

Jarrod West, Maumita Bhattacharya, Rafiqul Islam
2015 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
This paper presents a comprehensive investigation on financial fraud detection practices using such data mining methods, with a particular focus on computational intelligence-based techniques.  ...  Classification of the practices based on key aspects such as detection algorithm used, fraud type investigated, and success rate have been covered.  ...  Research on the performance of detection methods with respect to this factor is an area which needs further attention.  Generic framework: Given that there are many varieties of fraud, a generic framework  ... 
doi:10.1007/978-3-319-23802-9_16 fatcat:5vghiqbtfnaj3p6zaam3l3icta

Credit Card Fraud Detection using Deep Learning based on Auto-Encoder and Restricted Boltzmann Machine

Apapan Pumsirirat, Liu Yan
2018 International Journal of Advanced Computer Science and Applications  
This paper aims to 1) focus on fraud cases that cannot be detected based on previous history or supervised learning, 2) create a model of deep Auto-encoder and restricted Boltzmann machine (RBM) that can  ...  So, fraud detection systems need to detect online transactions by using unsupervised learning, because some fraudsters commit frauds once through online mediums and then switch to other techniques.  ...  A good fraud detection system should be able to identify the fraud transaction accurately and should make the detection possible in real-time transactions.  ... 
doi:10.14569/ijacsa.2018.090103 fatcat:7ryiptvyefbsbhstnz6puzjpc4

A Framework for Internal Fraud Risk Reduction at IT Integrating Business Processes: The IFR² Framework

Jans, Lybaert, Vanhoof
2009 International Journal of Digital Accounting Research  
A review of the academic literature learns that the academic community only addresses external fraud and how to detect this type of fraud.  ...  Fraud is a million dollar business and it is increasing every year. Both internal and external fraud present a substantial cost to our economy worldwide.  ...  Cahill et al. (2002) design a fraud signature, based on data of fraudulent calls, to detect telecommunications fraud.  ... 
doi:10.4192/1577-8517-v9_1 fatcat:i5yc7srftrdy3bn7xfz7nxoccm

Survey on Fraud Detection Techniques Using Data Mining

Muhammad Arif, Amil Roohani Dar
2015 International Journal of u- and e- Service, Science and Technology  
Fraud prevention is a continuing battle.  ...  Now a days, fraud is a million dollar business and every year it is increasing more and more.  ...  So for a long time the traditional ways of data analysis have been in use to detect fraud.  ... 
doi:10.14257/ijunesst.2015.8.3.15 fatcat:abchv64nlzge3eq5vopzdtg4vm

Research on the Accounting Fraud Approaches of Listed Companies in China

Lu Sun, Lin-lin Ren
2016 GLOBAL BUSINESS & FINANCE REVIEW  
) set conceptual framework of accounting fraud; (3) presents a profile of accounting fraud approaches by reviewing the selective sample of alleged accounting fraud cases from 2011-2015 by CSRC; (4) demonstrates  ...  A B S T R A C T After more than 20 years of vigorous development, there are more than 2,800 Chinese domestic listing companies by 2015, however, there is still endless stream of accounting fraud.  ...  The purpose is to offer a better reference for accounting fraud detecting and regulation. And our sample is based on the penalty of CSR over the five-year period from 2011-2015. Ⅱ.  ... 
doi:10.17549/gbfr.2017.22.1.1 fatcat:aroz47vixjampde56tsmfl7bcm
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